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Proceedings Paper

Feature extraction from photographic images using a hybrid neural network
Author(s): Vlatko Becanovic; Martin Kermit; Age J. Eide
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Paper Abstract

A new method for extracting features from photographic images has been developed. The input image is through a pulse coupled neural network transformed to a set of signatures, well suited for classification by unsupervised neural networks. A strategy using multiple self-organizing feature maps in a hierarchical manner is developed. With this approach, using a certain degree of supervision, an acceptable classification is obtained when applied to test images. The method is applied to license plate recognition.

Paper Details

Date Published: 22 March 1999
PDF: 11 pages
Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); doi: 10.1117/12.343053
Show Author Affiliations
Vlatko Becanovic, Royal Institute of Technology (Sweden)
Martin Kermit, Ostfold College (Norway)
Age J. Eide, Ostfold College (Norway)


Published in SPIE Proceedings Vol. 3728:
Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks
Thomas Lindblad; Mary Lou Padgett; Jason M. Kinser, Editor(s)

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